PureCycle Technologies (PCT) Total Liabilities (2020 - 2026)
PureCycle Technologies' Total Liabilities came in at $987.12 million for Q2 2026, up 4.6% from $943.6 million a year earlier and up 12.4% from the prior quarter.
PureCycle Technologies (PCT) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, PureCycle Technologies' Total Liabilities was $876.78 million, up 41.9% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of 24.2% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $617.94 million in FY2024 (-0.2%), $619.14 million in FY2023 (+76.7%), $350.45 million in FY2022 (+23.8%) and $283.15 million in FY2021 (-4.4%).
- The Q2 2026 figure represents the highest quarterly Total Liabilities in data going back to Q4 2020.
- Year-over-year, Total Liabilities has increased for six consecutive quarters, with growth averaging 40.1% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q2 2025 (growth of 120.4%), and the weakest in Q3 2024 (a decline of 12.5%).
- Business Quant data shows PCT's Total Liabilities at $878.58 million (Q1 2026), $876.78 million (Q4 2025) and $920.9 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Linde | 217.60 Bn | 200.72 Bn | 4.43 Bn | 47.73 Bn |
| 2 | Corning | 130.50 Bn | 123.63 Bn | 1.63 Bn | 19.83 Bn |
| 3 | Sherwin Williams | 80.80 Bn | 79.84 Bn | 3.34 Bn | 23.10 Bn |
| 4 | Air Products & Chemicals | 62.07 Bn | 59.97 Bn | 1.04 Bn | 23.85 Bn |
| 5 | Corteva | 51.85 Bn | 40.65 Bn | 3.66 Bn | 16.24 Bn |
| 6 | LyondellBasell Industries | 37.65 Bn | 27.27 Bn | 2.04 Bn | 23.80 Bn |
| 7 | Nutrien | 34.70 Bn | 31.57 Bn | 3.25 Bn | 27.62 Bn |
| 8 | Qnity Electronics | 26.13 Bn | 23.56 Bn | 666.00 Mn | 6.79 Bn |
| 9 | Ati | 24.61 Bn | 22.75 Bn | 309.80 Mn | 3.74 Bn |
| 10 | PureCycle Technologies | 936.22 Mn | 936.22 Mn | - | 987.12 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 987.12 Mn |
| Mar 31, 2026 | 878.58 Mn |
| Dec 31, 2025 | 876.78 Mn |
| Sep 30, 2025 | 920.90 Mn |
| Jun 30, 2025 | 943.60 Mn |
| Mar 31, 2025 | 549.13 Mn |
| Dec 31, 2024 | 617.94 Mn |
| Sep 30, 2024 | 547.36 Mn |
| Jun 30, 2024 | 428.14 Mn |
| Mar 31, 2024 | 397.18 Mn |
| Dec 31, 2023 | 619.14 Mn |
| Sep 30, 2023 | 625.42 Mn |
| Jun 30, 2023 | 457.58 Mn |
| Mar 31, 2023 | 387.86 Mn |
| Dec 31, 2022 | 350.45 Mn |
| Sep 30, 2022 | 368.55 Mn |
| Jun 30, 2022 | 335.55 Mn |
| Mar 31, 2022 | 335.59 Mn |
| Dec 31, 2021 | 283.15 Mn |
| Sep 30, 2021 | 361.81 Mn |
PureCycle Technologies Total Liabilities API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=total-liabilities&ticker=PCT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PCT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=PCT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();